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The Delivery of Multimedia Programmes Through LMS: An Australian ApproachSeah, Kenneth January 2005 (has links)
Australia's tertiary educational environment is changing; in the past decade, it has faced a new set of challenges and pressures (Cunningham et al., 1998) that are encroaching on the traditional definitions of what higher education is. These challenges often dictate the directions in which the tertiary education environment evolves into. Within the framework of institutional reforms, the adopted policies are often the best indicators of that transition. Flexible delivery or learning has been espoused as a means of meeting and mediating some of those challenges. With their emphasis on catering to the needs and expectations of the consumer in a consumerist society, flexible policies are becoming the norm in most institutes of higher learning. However, of interest within the structure of the flexible delivery approach is the development of learner management systems (LMS). The question is what are learner management systems? What do they represent and what do they offer to the learner that differentiates it from the traditional forms of learning? In its basic form, a learner management system is essentially a series of processes that are developed and organised so as to efficiently provide the learner with the required access and interaction required to facilitate his or her learning. However, what are the benefits of being aware of the capabilities and limitations afforded by such approaches? How does it contribute to the process of teaching and learning in the context of higher education? The effectiveness of how these learner management systems are used in context to its application in multimedia programmes is of importance. Institutions are progressively introducing similar learning systems into their delivery framework. The question as to whether a singular adaptive system or a customised option remains to be tested.
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Simulation of suicide tendency by using machine learningCalderon-Vilca, Hugo D., Wun-Rafael, William I., Miranda-Loarte, Roberto 07 1900 (has links)
El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Suicide is one of the most distinguished causes of death on the news worldwide. There are several factors and variables that can lead a person to commit this act, for example, stress, self-esteem, depression, among others. The causes and profiles of suicide cases are not revealed in detail by the competent institutions. We propose a simulation with a systematically generated dataset; such data reflect the adolescent population with suicidal tendency in Peru. We will evaluate three algorithms of supervised machine learning as a result of the algorithm C4.5 which is based on the trees to classify in a better way the suicidal tendency of adolescents. We finally propose a desktop tool that determines the suicidal tendency level of the adolescent. / Revisión por pares
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Potential based prediction markets : a machine learning perspectiveHu, Jinli January 2017 (has links)
A prediction market is a special type of market which offers trades for securities associated with future states that are observable at a certain time in the future. Recently, prediction markets have shown the promise of being an abstract framework for designing distributed, scalable and self-incentivized machine learning systems which could then apply to large scale problems. However, existing designs of prediction markets are far from achieving such machine learning goal, due to (1) the limited belief modelling power and also (2) an inadequate understanding of the market dynamics. This work is thus motivated by improving and extending current prediction market design in both aspects. This research is focused on potential based prediction markets, that is, prediction markets that are administered by potential (or cost function) based market makers (PMM). To improve the market’s modelling power, we first propose the partially-observable potential based market maker (PoPMM), which generalizes the standard PMM such that it allows securities to be defined and evaluated on future states that are only partially-observable, while also maintaining the key properties of the standard PMM. Next, we complete and extend the theory of generalized exponential families (GEFs), and use GEFs to free the belief models encoded in the PMM/PoPMM from always being in exponential families. To have a better understanding of the market dynamics and its link to model learning, we discuss the market equilibrium and convergence in two main settings: convergence driven by traders, and convergence driven by the market maker. In the former case, we show that a market-wise objective will emerge from the traders’ personal objectives and will be optimized through traders’ selfish behaviours in trading. We then draw intimate links between the convergence result to popular algorithms in convex optimization and machine learning. In the latter case, we augment the PMM with an extra belief model and a bid-ask spread, and model the market dynamics as an optimal control problem. This convergence result requires no specific models on traders, and is suitable for understanding the markets involving less controllable traders.
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Avaliação da aprendizagem na escola ciclada de Mato Grosso : o caso dos realtorios descritivos de avaliaçãoAmaral, Maria Clara Ede 22 February 2006 (has links)
Orientador: Luiz Carlos de Freitas / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Educação / Made available in DSpace on 2018-08-06T13:31:01Z (GMT). No. of bitstreams: 1
Amaral_MariaClaraEde_M.pdf: 9633918 bytes, checksum: 5b1c73fa95a1de1f461cbe9570c287a7 (MD5)
Previous issue date: 2006 / Mestrado / Ensino, Avaliação e Formação de Professores / Mestre em Educação
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Exploring conceptual knowledge and name relearning in semantic dementiaMayberry, Emily Jane January 2011 (has links)
This thesis investigated the role of the anterior temporal lobes (ATLs) in conceptual knowledge and name relearning by studying people with semantic dementia (SD). People with SD have atrophy focussed on the ATLs and they exhibit a pan-modal semantic impairment (e.g., Hodges, Patterson, Oxbury, & Funnell, 1992). Recent evidence suggests that modality-invariant concept representations are built up in the ATLs and that these modality-invariant representations are crucial for abstracting away from the surface features of items in order to generalise conceptual information based on their core semantic similarity (e.g., Lambon Ralph & Patterson, 2008). In order to test this, two of the studies described in this thesis (Chapters 2 and 3) assessed semantic generalisation in people with SD. These studies showed that people with SD are less able to generalise conceptual information on the basis of the deeper semantic structure of concepts but instead are increasingly influenced by the superficial similarity of the items. These studies support the hypothesis that the modality-invariant representations formed in the ATLs are crucial for semantic-based generalisation. Previous SD relearning studies have reported relatively good learning but a lack of generalisation to untrained items, tasks, and/or contexts (i.e., under-generalisation). This has been interpreted based on the Complementary Learning Systems (CLS) (McClelland, McNaughton, & O'Reilly, 1995) to suggest that the neocortical semantic system no longer makes a meaningful contribution to relearning but instead relearning is primarily dependent upon the sparse representational medial temporal lobe (MTL) learning system. The studies described in two of the thesis chapters (Chapters 4 and 5) investigated the role of the underlying systems further and found that the neocortical semantic system does still contribute to relearning in SD (although its contribution is disordered and based on the degraded concept representations in the ATL) but there is a shift in the division of labour such that the MTL system takes over more of the work. Finally, in order to clarify the outcomes of relearning in SD, Chapter 6 reviewed all of the previous SD relearning studies and confirmed that people with SD are able to relearn the specific information that they study but that this relearning is rigid. The review and a subsequent re-analysis of the data from Chapters 4 and 5 also showed that relearning in SD can have negative side-effects as well as positive effects.
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Increasing Inclusive Students' Achievement Through Use of USATestPrep's Integrated Learning SystemsElom, Roslynn Darnell 01 January 2017 (has links)
Integrated learning systems (ILS) are effective ways to increase academic achievement for students, including those with disabilities. However, many teachers do not fully or properly implement this type of educational technology in their classroom teaching. The purpose of this qualitative bounded case study was to examine the perceptions of high school educators and administrators toward ILS use. The study was grounded in Ely's conditions of change theory. Research questions focused on educators' perceptions of barriers toward implementation of an ILS in the classroom. Participants included 8 inclusive secondary school teachers and 2 local administrators in a rural school system in a southeastern U.S. state. Administrator participants were familiar with the ILS USATestPrep (UTP) and teacher participants had either limited or discontinued their use of that ILS in the classroom. Data were collected through the use of semi structured interviews and then analyzed for key themes. Findings showed that barriers of time, leadership, and available resources affected full implementation of the technological program in the local setting. Recommendations for future technology implementation included encouraging school leaders to provide teachers with time for implementation and pursue grant funding to minimize the impact of insufficient technological resources. Improving access to an ILS such as UTP may help teachers enhance the learning of students including those with disabilities and foster positive student successes and social change in the school and community environments.
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A Comparison of Users' Personal Information Sharing Awareness, Habits, and Practices in Social Networking Sites and E-Learning SystemsBall, Albert 01 January 2012 (has links)
Although reports of identity theft continue to be widely published, users continue to post an increasing amount of personal information online, especially within social networking sites (SNS) and e-learning systems (ELS). Research has suggested that many users lack awareness of the threats that risky online personal information sharing poses to their personal information. However, even among users who claim to be aware of security threats to their personal information, actual awareness of these security threats is often found to be lacking. Although attempts to raise users' awareness about the risks of sharing their personal information have become more common, it is unclear if users are unaware of the risks, or are simply unwilling or unable to protect themselves.
Research has also shown that users' habits may also have an influence on their practices. However, user behavior is complex, and the relationship between habit and practices is not clear. Habit theory has been validated across many disciplines, including psychology, genetics, and economics, with very limited attention in IS. Thus, the main goal of this study was to assess the influence of users' personal information sharing awareness (PISA) on their personal information sharing habits (PISH) and personal information sharing practices (PISP), as well as to compare the three constructs between SNS and ELS. Although habit has been studied significantly in other disciplines, a limited number of research studies have been conducted regarding IS usage and habit. Therefore, this study also investigated the influence of users' PISH on their PISP within the contexts of SNS and ELS. An empirical survey instrument was developed based on prior literature to collect and analyze data relevant to these three constructs. Path analysis was conducted on the data to determine the influence of users' PISA on their PISH and PISP, as well as the influence of users' PISH on their PISP. This study also utilized ANCOVA to determine if, and to what extent, any differences may exist between users' PISA, PISH, and PISP within SNS and ELS.
The survey was deployed to the student body and faculty members at a small private university in the Southeast United States; a total of 390 responses was received. Prior to final data analysis, pre-analysis data screening was performed to ensure the validity and accuracy of the collected data. Cronbach's Alpha was performed on PISA, PISH, and PISP, with all three constructs demonstrating high reliability. PISH was found to be the most significant factor evaluated in this study, as users' habits were determined to have the strongest influence on their PISP within the contexts of SNS and ELS.
The main contribution of this study was to advance the understanding of users' awareness of information security threats, their personal information sharing habits, and their personal information sharing practices. Information gained from this study may help organizations in the development of better approaches to the securing of users' personal information.
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Constructivist learning : an operational approach for designing adaptive learning environments supporting cognitive flexibilityVu Minh, Chieu 30 September 2005 (has links)
Constructivism is a learning theory that states that people learn by actively constructing their own knowledge, based on prior knowledge. Many different perspectives exist on constructivist pedagogical principles and on how to apply them to instructional design. It is thus not only difficult to evaluate the conformity of existing learning systems with constructivist principles, it is also quite hard to ensure that a new learning system being designed will ultimately facilitate and stimulate constructivist learning.
A critical characteristic often mentioned in learning systems is adaptability. That is, the ability to provide a learning experience that is continuously tailored to the needs of the individual learner.
The present research aims to help designing truly constructivist and adaptive learning systems. For that purpose, it is necessary to clarify what constructivism entails in an operational manner: I propose a set of criteria for certain aspects of constructivism and use it both as guidelines for designing learning systems and for evaluating the conformity of learning systems with these constructivist principles.
One facet often mentioned as being strongly relevant to constructivism is cognitive flexibility, meaning the ability to spontaneously restructure one's knowledge, in many ways, in adaptive response to radically changing situational demands.
The claim I make in the present thesis is that the operational approach I proposed makes the design and use of adaptive learning environments supporting cognitive flexibility straightforward and effective. More specifically, the dissertation makes four main contributions to the interdisciplinary field of learning and e-Learning technology.
Firstly, the thesis proposes operational criteria for cognitive flexibility and presents both justifications and examples of their use. The set of criteria may be used in different instructional situations for designing and evaluating conditions of learning.
Secondly, on the basis of the criteria for cognitive flexibility, the thesis proposes an operational instructional design process and shows an example of its use. The process may also be applied in a variety of instructional situations for the design and use of learning systems fostering cognitive flexibility.
Thirdly, the thesis introduces a new, open-source, domain-independent, Web-based adaptive e-Learning platform, named COFALE, and illustrates an example of its use. The platform may be used for designing adaptive learning systems supporting cognitive flexibility in various domains.
And fourthly, the thesis reports on a preliminary evaluation of the example handled by COFALE with actual learners. The study provides a certain number of encouraging results for fostering cognitive flexibility by means of ICT-based learning conditions.
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Evolutionary Design for Computational Visual AttentionBruce, Neil January 2003 (has links)
A new framework for simulating the visual attention system in primates is introduced. The proposed architecture is an abstraction of existing approaches influenced by the work of Koch and Ullman, and Tompa. Each stage of the attentional hierarchy is chosen with consideration for both psychophysics and mathematical optimality. A set of attentional operators are derived that act on basic image channels of intensity, hue and orientation to produce maps representing perceptual importance of each image pixel. The development of such operators is realized within the context of a genetic optimization. The model includes the notion of an information domain where feature maps are transformed to a domain that more closely corresponds to the human visual system. A careful analysis of various issues including feature extraction, density estimation and data fusion is presented within the context of the visual attention problem.
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Evolutionary Design for Computational Visual AttentionBruce, Neil January 2003 (has links)
A new framework for simulating the visual attention system in primates is introduced. The proposed architecture is an abstraction of existing approaches influenced by the work of Koch and Ullman, and Tompa. Each stage of the attentional hierarchy is chosen with consideration for both psychophysics and mathematical optimality. A set of attentional operators are derived that act on basic image channels of intensity, hue and orientation to produce maps representing perceptual importance of each image pixel. The development of such operators is realized within the context of a genetic optimization. The model includes the notion of an information domain where feature maps are transformed to a domain that more closely corresponds to the human visual system. A careful analysis of various issues including feature extraction, density estimation and data fusion is presented within the context of the visual attention problem.
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